The phrase, "It's a bird, it's a plane, it's Superman!" epitomizes the motivation for Kahneman, Treisman & Gibbs' (1992) influential object file theory. The point: the same object can appear different to an observer over multiple encounters, requiring token representations of spatiotemporal identity—persistence—independent from surface properties. One advantage of such token representations is that they can support the construction of tolerant long-term memories, what is often identified as the central problem in object recognition. Tagging persistence independent from surface appearance can teach an observer just how different an object can look from itself. What is a Superman such that it can look like a bird and a plane? To investigate this issue, we used apparent motion to manipulate the persistence of objects encountered during the incidental encoding phase of a long-term memory experiment. In all trials participants saw a single object repeated twice, either in a spatiotemporally continuous or discontinuous path. During a surprise test, participants viewed a stream that included old objects, similar objects, and completely new objects (relative to encoding). They were instructed to identify the status of each test object. Performance was significantly better for objects observed in a continuous motion stream during encoding. In a second experiment, each encounter during encoding was embedded in independent noise. We expected that object persistence should facilitate the combination of independently noisy encounters to produce tolerant memories. Indeed, during the surprise test phase, observers were more likely to correctly classify old objects perceived continuously and were also more likely to classify their similar foils as 'old.' Several control experiments and conditions precluded simple inattention-dependent accounts of the effects. These results suggest an important role for well-characterized features of online visual cognition in the construction of long-term object representations.